Statistical learning and multiple linear regression model for network selection using MIH

Award of Appreciation; International audience; A key requirement to provide seamless mobility and guaranteeing Quality of Service in heterogeneous environment is to select the best destination network during handover. In this paper, we propose a new schema for network selection based on Multiple Linear Regression Model (MLRM). A horough investigation, on a huge live data collected from GPRS/UMTS networks led to identify the Key Performance Indicators (KPIs) that play the most important role in the handover process. These KPIs are: Received Signal Code Power (RSCP), received energy per chip (Ec/No) and Available Bandwidth (ABW) of the destination network. To extract a handover model from col…